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<a href="_zero_one_loss_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno">    1</span><span class="comment">//===========================================================================</span><span class="comment"></span></div>
<div class="line"><a id="l00002" name="l00002"></a><span class="lineno">    2</span><span class="comment">/*!</span></div>
<div class="line"><a id="l00003" name="l00003"></a><span class="lineno">    3</span><span class="comment"> * </span></div>
<div class="line"><a id="l00004" name="l00004"></a><span class="lineno">    4</span><span class="comment"> *</span></div>
<div class="line"><a id="l00005" name="l00005"></a><span class="lineno">    5</span><span class="comment"> * \brief       Error measure for classication tasks, typically used for evaluation of results</span></div>
<div class="line"><a id="l00006" name="l00006"></a><span class="lineno">    6</span><span class="comment"> * </span></div>
<div class="line"><a id="l00007" name="l00007"></a><span class="lineno">    7</span><span class="comment"> * </span></div>
<div class="line"><a id="l00008" name="l00008"></a><span class="lineno">    8</span><span class="comment"> *</span></div>
<div class="line"><a id="l00009" name="l00009"></a><span class="lineno">    9</span><span class="comment"> * \author      T. Glasmachers</span></div>
<div class="line"><a id="l00010" name="l00010"></a><span class="lineno">   10</span><span class="comment"> * \date        2010-2011</span></div>
<div class="line"><a id="l00011" name="l00011"></a><span class="lineno">   11</span><span class="comment"> *</span></div>
<div class="line"><a id="l00012" name="l00012"></a><span class="lineno">   12</span><span class="comment"> *</span></div>
<div class="line"><a id="l00013" name="l00013"></a><span class="lineno">   13</span><span class="comment"> * \par Copyright 1995-2017 Shark Development Team</span></div>
<div class="line"><a id="l00014" name="l00014"></a><span class="lineno">   14</span><span class="comment"> * </span></div>
<div class="line"><a id="l00015" name="l00015"></a><span class="lineno">   15</span><span class="comment"> * &lt;BR&gt;&lt;HR&gt;</span></div>
<div class="line"><a id="l00016" name="l00016"></a><span class="lineno">   16</span><span class="comment"> * This file is part of Shark.</span></div>
<div class="line"><a id="l00017" name="l00017"></a><span class="lineno">   17</span><span class="comment"> * &lt;https://shark-ml.github.io/Shark/&gt;</span></div>
<div class="line"><a id="l00018" name="l00018"></a><span class="lineno">   18</span><span class="comment"> * </span></div>
<div class="line"><a id="l00019" name="l00019"></a><span class="lineno">   19</span><span class="comment"> * Shark is free software: you can redistribute it and/or modify</span></div>
<div class="line"><a id="l00020" name="l00020"></a><span class="lineno">   20</span><span class="comment"> * it under the terms of the GNU Lesser General Public License as published </span></div>
<div class="line"><a id="l00021" name="l00021"></a><span class="lineno">   21</span><span class="comment"> * by the Free Software Foundation, either version 3 of the License, or</span></div>
<div class="line"><a id="l00022" name="l00022"></a><span class="lineno">   22</span><span class="comment"> * (at your option) any later version.</span></div>
<div class="line"><a id="l00023" name="l00023"></a><span class="lineno">   23</span><span class="comment"> * </span></div>
<div class="line"><a id="l00024" name="l00024"></a><span class="lineno">   24</span><span class="comment"> * Shark is distributed in the hope that it will be useful,</span></div>
<div class="line"><a id="l00025" name="l00025"></a><span class="lineno">   25</span><span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span></div>
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno">   26</span><span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the</span></div>
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno">   27</span><span class="comment"> * GNU Lesser General Public License for more details.</span></div>
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno">   28</span><span class="comment"> * </span></div>
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno">   29</span><span class="comment"> * You should have received a copy of the GNU Lesser General Public License</span></div>
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno">   30</span><span class="comment"> * along with Shark.  If not, see &lt;http://www.gnu.org/licenses/&gt;.</span></div>
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno">   31</span><span class="comment"> *</span></div>
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno">   32</span><span class="comment"> */</span></div>
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno">   33</span> </div>
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno">   34</span><span class="preprocessor">#ifndef SHARK_OBJECTIVEFUNCTIONS_LOSS_ZEROONELOSS_H</span></div>
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno">   35</span><span class="preprocessor">#define SHARK_OBJECTIVEFUNCTIONS_LOSS_ZEROONELOSS_H</span></div>
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno">   36</span> </div>
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno">   37</span> </div>
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno">   38</span><span class="preprocessor">#include &lt;<a class="code" href="_abstract_loss_8h.html" title="super class of all loss functions">shark/ObjectiveFunctions/Loss/AbstractLoss.h</a>&gt;</span></div>
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno">   39</span> </div>
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno">   40</span><span class="keyword">namespace </span><a class="code hl_namespace" href="namespaceshark.html" title="AbstractMultiObjectiveOptimizer.">shark</a> {</div>
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno">   41</span><span class="comment"></span> </div>
<div class="line"><a id="l00042" name="l00042"></a><span class="lineno">   42</span><span class="comment">///</span></div>
<div class="line"><a id="l00043" name="l00043"></a><span class="lineno">   43</span><span class="comment">/// \brief 0-1-loss for classification.</span></div>
<div class="line"><a id="l00044" name="l00044"></a><span class="lineno">   44</span><span class="comment">///</span></div>
<div class="line"><a id="l00045" name="l00045"></a><span class="lineno">   45</span><span class="comment">/// The ZeroOneLoss requires the existence of the comparison</span></div>
<div class="line"><a id="l00046" name="l00046"></a><span class="lineno">   46</span><span class="comment">/// operator == for its LabelType template parameter. The</span></div>
<div class="line"><a id="l00047" name="l00047"></a><span class="lineno">   47</span><span class="comment">/// loss function returns zero of the predictions exactly</span></div>
<div class="line"><a id="l00048" name="l00048"></a><span class="lineno">   48</span><span class="comment">/// matches the label, and one otherwise.</span></div>
<div class="line"><a id="l00049" name="l00049"></a><span class="lineno">   49</span><span class="comment">/// \ingroup lossfunctions</span></div>
<div class="line"><a id="l00050" name="l00050"></a><span class="lineno">   50</span><span class="comment"></span><span class="keyword">template</span>&lt;<span class="keyword">class</span> LabelType = <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span>, <span class="keyword">class</span> OutputType = LabelType&gt;</div>
<div class="foldopen" id="foldopen00051" data-start="{" data-end="};">
<div class="line"><a id="l00051" name="l00051"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss.html">   51</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_zero_one_loss.html" title="0-1-loss for classification.">ZeroOneLoss</a> : <span class="keyword">public</span> <a class="code hl_class" href="classshark_1_1_abstract_loss.html" title="Loss function interface.">AbstractLoss</a>&lt;LabelType, LabelType&gt;</div>
<div class="line"><a id="l00052" name="l00052"></a><span class="lineno">   52</span>{</div>
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno">   53</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno">   54</span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_abstract_loss.html" title="Loss function interface.">AbstractLoss&lt;LabelType, LabelType&gt;</a> <a class="code hl_class" href="classshark_1_1_abstract_loss.html" title="Loss function interface.">base_type</a>;</div>
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss.html#ab43603f1f7774b72b2178946e6485eeb">   55</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a6e6cc93c4d6599c219d396dcab81e938">base_type::BatchLabelType</a> <a class="code hl_typedef" href="classshark_1_1_zero_one_loss.html#ab43603f1f7774b72b2178946e6485eeb">BatchLabelType</a>;</div>
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss.html#adac2c5c0e4fd170d44d604e663ec30d6">   56</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">base_type::BatchOutputType</a> <a class="code hl_typedef" href="classshark_1_1_zero_one_loss.html#adac2c5c0e4fd170d44d604e663ec30d6">BatchOutputType</a>;</div>
<div class="line"><a id="l00057" name="l00057"></a><span class="lineno">   57</span><span class="comment"></span> </div>
<div class="line"><a id="l00058" name="l00058"></a><span class="lineno">   58</span><span class="comment">    /// constructor</span></div>
<div class="foldopen" id="foldopen00059" data-start="{" data-end="}">
<div class="line"><a id="l00059" name="l00059"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss.html#a62edff532f2bea68a6a2313d4031dd76">   59</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_zero_one_loss.html#a62edff532f2bea68a6a2313d4031dd76" title="constructor">ZeroOneLoss</a>()</div>
<div class="line"><a id="l00060" name="l00060"></a><span class="lineno">   60</span>    { }</div>
</div>
<div class="line"><a id="l00061" name="l00061"></a><span class="lineno">   61</span> </div>
<div class="line"><a id="l00062" name="l00062"></a><span class="lineno">   62</span><span class="comment"></span> </div>
<div class="line"><a id="l00063" name="l00063"></a><span class="lineno">   63</span><span class="comment">    /// \brief From INameable: return the class name.</span></div>
<div class="foldopen" id="foldopen00064" data-start="{" data-end="}">
<div class="line"><a id="l00064" name="l00064"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss.html#ae78565cab68eb04269cf2cd1b4b7bca2">   64</a></span><span class="comment"></span>    std::string <a class="code hl_function" href="classshark_1_1_zero_one_loss.html#ae78565cab68eb04269cf2cd1b4b7bca2" title="From INameable: return the class name.">name</a>()<span class="keyword"> const</span></div>
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno">   65</span><span class="keyword">    </span>{ <span class="keywordflow">return</span> <span class="stringliteral">&quot;ZeroOneLoss&quot;</span>; }</div>
</div>
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno">   66</span> </div>
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno">   67</span>    <span class="keyword">using </span><a class="code hl_function" href="classshark_1_1_abstract_loss.html#ad57cb10f610d506e522f707563acabb8" title="evaluate the loss for a batch of targets and a prediction">base_type::eval</a>;</div>
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno">   68</span><span class="comment"></span> </div>
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno">   69</span><span class="comment">    ///\brief Return zero if labels == predictions and one otherwise.</span></div>
<div class="foldopen" id="foldopen00070" data-start="{" data-end="}">
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss.html#acba6670d53701d50eed0ecdbc1114175">   70</a></span><span class="comment"></span>    <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_zero_one_loss.html#acba6670d53701d50eed0ecdbc1114175" title="Return zero if labels == predictions and one otherwise.">eval</a>(<a class="code hl_typedef" href="classshark_1_1_zero_one_loss.html#ab43603f1f7774b72b2178946e6485eeb">BatchLabelType</a> <span class="keyword">const</span>&amp; labels, <a class="code hl_typedef" href="classshark_1_1_zero_one_loss.html#adac2c5c0e4fd170d44d604e663ec30d6">BatchOutputType</a> <span class="keyword">const</span>&amp; predictions)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno">   71</span>        std::size_t numInputs = labels.size();</div>
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno">   72</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(numInputs == predictions.size());</div>
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno">   73</span> </div>
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno">   74</span>        <span class="keywordtype">double</span> error = 0;</div>
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno">   75</span>        <span class="keywordflow">for</span>(std::size_t i = 0; i != numInputs; ++i){</div>
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno">   76</span>            error += (predictions(i) != labels(i))?1.0:0.0;</div>
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno">   77</span>        }</div>
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno">   78</span>        <span class="keywordflow">return</span> error;</div>
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno">   79</span>    }</div>
</div>
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno">   80</span>};</div>
</div>
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno">   81</span> </div>
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno">   82</span><span class="comment"></span> </div>
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno">   83</span><span class="comment">/// \brief 0-1-loss for classification.</span></div>
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno">   84</span><span class="comment"></span><span class="keyword">template</span> &lt;<span class="keyword">class</span> Float&gt;</div>
<div class="foldopen" id="foldopen00085" data-start="{" data-end="};">
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html">   85</a></span><span class="keyword">class </span><a class="code hl_class" href="classshark_1_1_zero_one_loss.html" title="0-1-loss for classification.">ZeroOneLoss</a>&lt;unsigned int, blas::vector&lt;Float&gt; &gt; : <span class="keyword">public</span> <a class="code hl_class" href="classshark_1_1_abstract_loss.html" title="Loss function interface.">AbstractLoss</a>&lt;unsigned int, blas::vector&lt;Float&gt; &gt;</div>
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno">   86</span>{</div>
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno">   87</span><span class="keyword">public</span>:</div>
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno">   88</span>    <span class="keyword">typedef</span> <a class="code hl_class" href="classshark_1_1_abstract_loss.html" title="Loss function interface.">AbstractLoss&lt;unsigned int, blas::vector&lt;Float&gt;</a> &gt; <a class="code hl_class" href="classshark_1_1_abstract_loss.html">base_type</a>;</div>
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#a420c0aeacacb743e68ba44e6f7ef6005">   89</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#a6e6cc93c4d6599c219d396dcab81e938">base_type::BatchLabelType</a> <a class="code hl_typedef" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#a420c0aeacacb743e68ba44e6f7ef6005">BatchLabelType</a>;</div>
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#aa2436ce8cb86ce9f7d88622a452affdb">   90</a></span>    <span class="keyword">typedef</span> <span class="keyword">typename</span> <a class="code hl_typedef" href="classshark_1_1_abstract_loss.html#ac3a1a01831f11b5357d6005837ac245b">base_type::BatchOutputType</a> <a class="code hl_typedef" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#aa2436ce8cb86ce9f7d88622a452affdb">BatchOutputType</a>;</div>
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno">   91</span><span class="comment"></span> </div>
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno">   92</span><span class="comment">    /// constructor</span></div>
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno">   93</span><span class="comment">    ///</span></div>
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno">   94</span><span class="comment">    /// \param threshold: in the case dim(predictions) == 1, predictions strictly larger than this parameter are regarded as belonging to the positive class</span></div>
<div class="foldopen" id="foldopen00095" data-start="{" data-end="}">
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#a5deb4b62f0a3cc011c6297b9b40752a7">   95</a></span><span class="comment"></span>    <a class="code hl_function" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#a5deb4b62f0a3cc011c6297b9b40752a7">ZeroOneLoss</a>(<span class="keywordtype">double</span> threshold = 0.0)</div>
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno">   96</span>    {</div>
<div class="line"><a id="l00097" name="l00097"></a><span class="lineno">   97</span>        m_threshold = threshold;</div>
<div class="line"><a id="l00098" name="l00098"></a><span class="lineno">   98</span>    }</div>
</div>
<div class="line"><a id="l00099" name="l00099"></a><span class="lineno">   99</span><span class="comment"></span> </div>
<div class="line"><a id="l00100" name="l00100"></a><span class="lineno">  100</span><span class="comment">    /// \brief From INameable: return the class name.</span></div>
<div class="foldopen" id="foldopen00101" data-start="{" data-end="}">
<div class="line"><a id="l00101" name="l00101"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#a06650f85d667aacb16546f910b5e16b4">  101</a></span><span class="comment"></span>    std::string <a class="code hl_function" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#a06650f85d667aacb16546f910b5e16b4" title="From INameable: return the class name.">name</a>()<span class="keyword"> const</span></div>
<div class="line"><a id="l00102" name="l00102"></a><span class="lineno">  102</span><span class="keyword">    </span>{ <span class="keywordflow">return</span> <span class="stringliteral">&quot;ZeroOneLoss&quot;</span>; }</div>
</div>
<div class="line"><a id="l00103" name="l00103"></a><span class="lineno">  103</span> </div>
<div class="line"><a id="l00104" name="l00104"></a><span class="lineno">  104</span> </div>
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno">  105</span>    <span class="comment">// annoyingness of C++ templates</span></div>
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno">  106</span>    <span class="keyword">using </span><a class="code hl_function" href="classshark_1_1_abstract_loss.html#ad57cb10f610d506e522f707563acabb8" title="evaluate the loss for a batch of targets and a prediction">base_type::eval</a>;</div>
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno">  107</span><span class="comment"></span> </div>
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno">  108</span><span class="comment">    /// Return zero if labels == arg max { predictions_i } and one otherwise,</span></div>
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno">  109</span><span class="comment">    /// where the index i runs over the components of the predictions vector.</span></div>
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno">  110</span><span class="comment">    /// A special version of dim(predictions) == 1 computes the predicted</span></div>
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno">  111</span><span class="comment">    /// labels by thresholding at zero. Shark&#39;s label convention is used,</span></div>
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno">  112</span><span class="comment">    /// saying that a positive value encodes class 0, a negative value</span></div>
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno">  113</span><span class="comment">    /// encodes class 1.</span></div>
<div class="foldopen" id="foldopen00114" data-start="{" data-end="}">
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#a392993dc623f198949955e4fdb5b9d2a">  114</a></span><span class="comment"></span>    <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#a392993dc623f198949955e4fdb5b9d2a">eval</a>(<a class="code hl_typedef" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#a420c0aeacacb743e68ba44e6f7ef6005">BatchLabelType</a> <span class="keyword">const</span>&amp; labels, <a class="code hl_typedef" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#aa2436ce8cb86ce9f7d88622a452affdb">BatchOutputType</a> <span class="keyword">const</span>&amp; predictions)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno">  115</span>        std::size_t numInputs = labels.size();</div>
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno">  116</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(numInputs == predictions.size1());</div>
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno">  117</span> </div>
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno">  118</span>        <span class="keywordtype">double</span> error = 0;</div>
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno">  119</span>        <span class="keywordflow">for</span>(std::size_t i = 0; i != numInputs; ++i){</div>
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno">  120</span>            error+=evalSingle(labels(i),row(predictions,i));</div>
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno">  121</span>        }</div>
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno">  122</span>        <span class="keywordflow">return</span> error;</div>
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno">  123</span>    }</div>
</div>
<div class="line"><a id="l00124" name="l00124"></a><span class="lineno">  124</span>    </div>
<div class="foldopen" id="foldopen00125" data-start="{" data-end="}">
<div class="line"><a id="l00125" name="l00125"></a><span class="lineno"><a class="line" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#ad29ef56602b3431b411320d95434a0ac">  125</a></span>    <span class="keywordtype">double</span> <a class="code hl_function" href="classshark_1_1_zero_one_loss_3_01unsigned_01int_00_01blas_1_1vector_3_01_float_01_4_01_4.html#ad29ef56602b3431b411320d95434a0ac">eval</a>(<a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data&lt;unsigned int&gt;</a> <span class="keyword">const</span>&amp; targets, <a class="code hl_class" href="classshark_1_1_data.html" title="Data container.">Data</a>&lt; blas::vector&lt;Float&gt;&gt; <span class="keyword">const</span>&amp; predictions, RealVector <span class="keyword">const</span>&amp; weights)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00126" name="l00126"></a><span class="lineno">  126</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(predictions.numberOfElements() == weights.size());</div>
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno">  127</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(targets.<a class="code hl_function" href="group__shark__globals.html#ga814e8b0028cc90dd2af69805e8f8a04d" title="Returns the total number of elements.">numberOfElements</a>() == weights.size());</div>
<div class="line"><a id="l00128" name="l00128"></a><span class="lineno">  128</span>        <a class="code hl_define" href="_exception_8h.html#a42a6a50e4d06c00d60fbca5333f40768">SIZE_CHECK</a>(predictions.numberOfBatches() == targets.<a class="code hl_function" href="group__shark__globals.html#gabd82edf467b9b82f4b0a1e70fd695311" title="Returns the number of batches of the set.">numberOfBatches</a>());</div>
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno">  129</span>        <span class="keywordtype">double</span> error = 0;</div>
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno">  130</span>        <span class="keywordflow">for</span>(std::size_t i = 0; i != predictions.numberOfBatches(); ++i){</div>
<div class="line"><a id="l00131" name="l00131"></a><span class="lineno">  131</span>            <span class="keywordflow">for</span>(std::size_t j = 0; j != targets.<a class="code hl_function" href="group__shark__globals.html#ga73034ee5639176b0d45e1059859d0f0a">batch</a>(i).size(); ++j){</div>
<div class="line"><a id="l00132" name="l00132"></a><span class="lineno">  132</span>                error+= weights(i) * evalSingle(targets.<a class="code hl_function" href="group__shark__globals.html#ga73034ee5639176b0d45e1059859d0f0a">batch</a>(i)(j),row(predictions.batch(i),j));</div>
<div class="line"><a id="l00133" name="l00133"></a><span class="lineno">  133</span>            }</div>
<div class="line"><a id="l00134" name="l00134"></a><span class="lineno">  134</span>        }</div>
<div class="line"><a id="l00135" name="l00135"></a><span class="lineno">  135</span>        <span class="keywordflow">return</span> error / weights.size();</div>
<div class="line"><a id="l00136" name="l00136"></a><span class="lineno">  136</span>    }</div>
</div>
<div class="line"><a id="l00137" name="l00137"></a><span class="lineno">  137</span>    </div>
<div class="line"><a id="l00138" name="l00138"></a><span class="lineno">  138</span><span class="keyword">private</span>:</div>
<div class="line"><a id="l00139" name="l00139"></a><span class="lineno">  139</span>    <span class="keyword">template</span>&lt;<span class="keyword">class</span> VectorType&gt;</div>
<div class="line"><a id="l00140" name="l00140"></a><span class="lineno">  140</span>    <span class="keywordtype">double</span> evalSingle(<span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> label, <a class="code hl_typedef" href="_c_svm_linear_8cpp.html#ab106d665148183a2dc94dcf8716c9203">VectorType</a> <span class="keyword">const</span>&amp; predictions)<span class="keyword"> const</span>{</div>
<div class="line"><a id="l00141" name="l00141"></a><span class="lineno">  141</span>        std::size_t size = predictions.size();</div>
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno">  142</span>        <span class="keywordflow">if</span> (size == 1){</div>
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno">  143</span>            <span class="comment">// binary case, single real-valued predictions</span></div>
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno">  144</span>            <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> t = (predictions(0) &gt; m_threshold);</div>
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno">  145</span>            <span class="keywordflow">if</span> (t == label) <span class="keywordflow">return</span> 0.0;</div>
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno">  146</span>            <span class="keywordflow">else</span> <span class="keywordflow">return</span> 1.0;</div>
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno">  147</span>        }</div>
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno">  148</span>        <span class="keywordflow">else</span>{</div>
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno">  149</span>            <span class="comment">// multi-class case, one prediction component per class</span></div>
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno">  150</span>            <a class="code hl_define" href="_exception_8h.html#abd848215f138fc44f696aecb3e417e6c">RANGE_CHECK</a>(label &lt; size);</div>
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno">  151</span>            <span class="keywordtype">double</span> p = predictions(label);</div>
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno">  152</span>            <span class="keywordflow">for</span> (std::size_t i = 0; i&lt;size; i++)</div>
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno">  153</span>            {</div>
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno">  154</span>                <span class="keywordflow">if</span> (i == label) <span class="keywordflow">continue</span>;</div>
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno">  155</span>                <span class="keywordflow">if</span> (predictions(i) &gt;= p) <span class="keywordflow">return</span> 1.0;</div>
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno">  156</span>            }</div>
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno">  157</span>            <span class="keywordflow">return</span> 0.0;</div>
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno">  158</span>        }</div>
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno">  159</span>    }</div>
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno">  160</span> </div>
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno">  161</span>    <span class="keywordtype">double</span> m_threshold; <span class="comment">///&lt; in the case dim(predictions) == 1, predictions strictly larger tha this parameter are regarded as belonging to the positive class</span></div>
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno">  162</span>};</div>
</div>
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno">  163</span> </div>
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno">  164</span> </div>
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno">  165</span>}</div>
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno">  166</span><span class="preprocessor">#endif</span></div>
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